Research On Wireless Remote Monitoring And Data Analysis Of Fertilizer Spreade

With the increasing application of informatization in agricultural production processes,and with social development and technological progress,the rapid transformation from traditional agricultural production to fully mechanized agricultural production and then to unmanned agricultural production has been accelerated.The CAN bus system is widely used in large tractor equipment in China,and is equipped with a tractor monitoring system to monitor tractor operating parameters and status in real-time,providing an information foundation for tractor operation and management.In response to the problems of insufficient monitoring information,non-standard management,and lack of effective monitoring in the monitoring and management of agricultural machinery operations,a wireless remote data monitoring system for fertilization machines was studied.The main research work is as follows:(1)The agricultural machinery CAN bus technology and the Internet of Things technology are integrated.The edge computing gateway is used to analyze,process and calculate the CAN data sent by the sensor,and then the storage module in the gateway is used to store it.The application of edge technology can achieve edge monitoring and human intervention of data,and the display screen matched with the gateway can enable operators to view job parameters in real-time.At the same time,the data stored in the gateway is transformed and encapsulated based on transmission protocols,and the wireless communication module built-in in the gateway is used to transmit the data to the cloud,and the data in the cloud historical database is visualized and processed.(2)The data visualization application is developed through the cloud platform to visually process and display the data received by the platform.The monitoring personnel can view the operation trajectory of the fertilizer applicator in real-time,and view the real-time operation screen of the fertilizer applicator through network high-definition cameras installed on both sides of the fertilizer applicator,and archive video data and parameter data in the cloud.(3)To accurately measure the field operation data of the fertilizer applicator,the Kalman filtering algorithm is used to improve the accuracy of the data collected by the GNSS receiver,and then the Gaussian projection algorithm is used to calculate the working area of the fertilizer applicator.And bring the calculated area into the fertilization algorithm to obtain the fertilization amount data for the fertilization machine operation.(4)After field experiments,the data transmission success rate and average data transmission delay of the wireless remote monitoring system were used as test indicators.The experimental data transmitted to the cloud was analyzed and compared with the data exported through the built-in SD card of the gateway.At the same time,the data uploaded to the platform was visualized and processed.The experimental results show that the average data transmission delay of the system is 1 second,and the data successfully uploaded to the cloud is over 99%.The performance is stable and meets the needs of field operations.The research results indicate that the longitude and latitude data,speed,elevation,real-time images generated during the operation of the fertilizer applicator,as well as the data collected by various sensors in the fertilizer applicator,are transmitted and stored in real-time through a wireless remote monitoring system,and the data is visualized and processed through a cloud platform.It has achieved full monitoring and real-time tracking of the operation process of the fertilizer applicator,enabling agricultural machinery practitioners to control the operation of the fertilizer applicator in real time.